Executive Summary Lead Authors: SOCCR Coordinating Team
Bibliographic record
Abstract
The Earth’s carbon budget is in imbalance. Beginning with the Industrial Revolution in the 18th century, but most dramatically since World War II, the human use of coal, petroleum, and natural gas has released large amounts of carbon from geological deposits to the atmosphere, primarily as the combustion product carbon dioxide (CO2). Clearing of forests and plowing of grasslands for agriculture has also released carbon from plants and soils to the atmosphere as CO2. The combined rate of release is far larger than can be balanced by the biological and geological processes that naturally remove CO2 from the atmosphere and store it in various terrestrial and marine reservoirs as part of the earth’s carbon cycle. Although the oceans have taken up a large fraction of the CO2 released through human activity, much of it has “piled up ” in the atmosphere, as demonstrated by the dramatic increase in the atmospheric concentration of CO2. The concentration has increased by 31 % since 1750, and the present concentration is now higher than at any time in the past 420,000 years and perhaps the past 20 million years. Because CO2 is an important greenhouse gas, this imbalance and buildup in the atmosphere has consequences for climate and climate change. North America is a major contributor to this imbalance. Among all countries, the United States, Canada, and Mexico ranked, respectively, as the first, eighth, and eleventh largest emitters of CO2 from
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.396 | 0.266 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".